Decline of onset-to-diagnosis interval and its impacts on clinical outcome of COVID-19 in China: a nation-wide observational study.

BACKGROUND: To quantitatively assess the impact of the onset-to-diagnosis interval (ODI) on severity and death for coronavirus disease 2019 (COVID-19) patients. METHODS: This retrospective study was conducted based on the data on COVID-19 cases of China over the age of 40 years reported through China's National Notifiable Infectious Disease Surveillance System from February 5, 2020 to October 8, 2020. The impacts of ODI on severe rate (SR) and case fatality rate (CFR) were evaluated at individual and population levels, which was further disaggregated by sex, age and geographic origin. RESULTS: As the rapid decline of ODI from around 40 days in early January to < 3 days in early March, both CFR and SR of COVID-19 largely dropped below 5% in China. After adjusting for age, sex, and region, an effect of ODI on SR was observed with the highest OR of 2.95 (95% CI 2.37‒3.66) at Day 10-11 and attributable fraction (AF) of 29.1% (95% CI 22.2‒36.1%) at Day 8-9. However, little effect of ODI on CFR was observed. Moreover, discrepancy of effect magnitude was found, showing a greater effect from ODI on SR among patients of male sex, younger age, and those cases in Wuhan. CONCLUSION: The ODI was significantly associated with the severity of COVID-19, highlighting the importance of timely diagnosis, especially for patients who were confirmed to gain increased benefit from early diagnosis to some extent.

Electrostatic Interactions Are the Primary Determinant of the Binding Affinity of SARS-CoV-2 Spike RBD to ACE2: A Computational Case Study of Omicron Variants.

To explore the mechanistic origin that determines the binding affinity of SARS-CoV-2 spike receptor binding domain (RBD) to human angiotensin converting enzyme 2 (ACE2), we constructed the homology models of RBD-ACE2 complexes of four Omicron subvariants (BA.1, BA.2, BA.3 and BA.4/5), and compared them with wild type complex (RBDWT-ACE2) in terms of various structural dynamic properties by molecular dynamics (MD) simulations and binding free energy (BFE) calculations. The results of MD simulations suggest that the RBDs of all the Omicron subvariants (RBDOMIs) feature increased global structural fluctuations when compared with RBDWT. Detailed comparison of BFE components reveals that the enhanced electrostatic attractive interactions are the main determinant of the higher ACE2-binding affinity of RBDOMIs than RBDWT, while the weakened electrostatic attractive interactions determine RBD of BA.4/5 subvariant (RBDBA.4/5) lowest ACE2-binding affinity among all Omicron subvariants. The per-residue BFE decompositions and the hydrogen bond (HB) networks analyses indicate that the enhanced electrostatic attractive interactions are mainly through gain/loss of the positively/negatively charged residues, and the formation or destruction of the interfacial HBs and salt bridges can also largely affect the ACE2-binding affinity of RBD. It is worth pointing out that since Q493R plays the most important positive contribution in enhancing binding affinity, the absence of this mutation in RBDBA.4/5 results in a significantly weaker binding affinity to ACE2 than other Omicron subvariants. Our results provide insight into the role of electrostatic interactions in determining of the binding affinity of SARS-CoV-2 RBD to human ACE2.

A variant-proof SARS-CoV-2 vaccine targeting HR1 domain in S2 subunit of spike protein.

The emerging SARS-CoV-2 variants, commonly with many mutations in S1 subunit of spike (S) protein are weakening the efficacy of the current vaccines and antibody therapeutics. This calls for the variant-proof SARS-CoV-2 vaccines targeting the more conserved regions in S protein. Here, we designed a recombinant subunit vaccine, HR121, targeting the conserved HR1 domain in S2 subunit of S protein. HR121 consisting of HR1-linker1-HR2-linker2-HR1, is conformationally and functionally analogous to the HR1 domain present in the fusion intermediate conformation of S2 subunit. Immunization with HR121 in rabbits and rhesus macaques elicited highly potent cross-neutralizing antibodies against SARS-CoV-2 and its variants, particularly Omicron sublineages. Vaccination with HR121 achieved near-full protections against prototype SARS-CoV-2 infection in hACE2 transgenic mice, Syrian golden hamsters and rhesus macaques, and effective protection against Omicron BA.2 infection in Syrian golden hamsters. This study demonstrates that HR121 is a promising candidate of variant-proof SARS-CoV-2 vaccine with a novel conserved target in the S2 subunit for application against current and future SARS-CoV-2 variants.

Transmembrane serine protease TMPRSS2 implicated in SARS-CoV-2 infection is autoactivated intracellularly and requires N-glycosylation for regulation.

Transmembrane protease serine 2 (TMPRSS2) is a membrane-bound protease expressed in many human epithelial tissues, including the airway and lung. TMPRSS2-mediated cleavage of viral spike protein is a key mechanism in severe acute respiratory syndrome coronavirus 2 activation and host cell entry. To date, the cellular mechanisms that regulate TMPRSS2 activity and cell surface expression are not fully characterized. In this study, we examined two major post-translational events, zymogen activation and N-glycosylation, in human TMPRSS2. In experiments with human embryonic kidney 293, bronchial epithelial 16HBE, and lung alveolar epithelial A549 cells, we found that TMPRSS2 was activated via intracellular autocatalysis and that this process was blocked in the presence of hepatocyte growth factor activator inhibitors 1 and 2. By glycosidase digestion and site-directed mutagenesis, we showed that human TMPRSS2 was N-glycosylated. N-glycosylation at an evolutionarily conserved site in the scavenger receptor cysteine-rich domain was required for calnexin-assisted protein folding in the endoplasmic reticulum and subsequent intracellular trafficking, zymogen activation, and cell surface expression. Moreover, we showed that TMPRSS2 cleaved severe acute respiratory syndrome coronavirus 2 spike protein intracellularly in human embryonic kidney 293 cells. These results provide new insights into the cellular mechanism in regulating TMPRSS2 biosynthesis and function. Our findings should help to understand the role of TMPRSS2 in major respiratory viral diseases.

Real-time detection of viruses in aerosols with weak light imaging based on Tesla discharge

The analysis and detection of nucleic acid and specific antigens and antibodies are the most basic technologies for virus monitoring. However, the potential window for applying these technologies exists within a late specific period in the early monitoring and control of unknown viruses, especially human and animal pathogenic viruses transmitted via aerosols, e.g., SARS-CoV-2 and its variants. This is because early, real-time, and convenient monitoring of unknown viruses in the air or exhaled gas cannot be directly achieved through existing technologies. Herein, we report a weak light spectral imaging technology based on Tesla discharge (termed T-DAI) that can quickly monitor for viruses in real time in simulated aerosols with 71% sensitivity and 76% specificity for aerosol virus concentrations exceeding approximately 2800 vp/μl. This technology realizes the rapid detection of low concentrations of viruses in aerosols and could provide an important means for predicting, screening, and monitoring unknown or pandemic pathogenic viruses in the air or exhaled breath of humans and animals. [ FROM AUTHOR] Copyright of Applied Physics Letters is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Anisodamine potently inhibits SARS-CoV-2 infection in vitro and targets its main protease.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) provoked a pandemic of acute respiratory disease, namely coronavirus disease 2019 (COVID-19). Currently, effective drugs for this disease are urgently warranted. Anisodamine is a traditional Chinese medicine that is predicted as a potential therapeutic drug for the treatment of COVID-19. Therefore, this study aimed to investigate its antiviral activity and crucial targets in SARS-CoV-2 infection. SARS-CoV-2 and anisodamine were co-cultured in Vero E6 cells, and the antiviral activity of anisodamine was assessed by immunofluorescence assay. The antiviral activity of anisodamine was further measured by pseudovirus entry assay in HEK293/hACE2 cells. Finally, the predictions of crucial targets of anisodamine on SARS-CoV-2 were analyzed by molecular docking studies. We discovered that anisodamine suppressed SARS-CoV-2 infection in Vero E6 cells, and reduced the SARS-CoV-2 pseudovirus entry to HEK293/hACE2 cells. Furthermore, molecular docking studies indicated that anisodamine may target SARS-CoV-2 main protease (Mpro) with the docking score of -6.63 kcal/mol and formed three H-bonds with Gly143, Cys145, and Cys44 amino acid residues at the predicted active site of Mpro. This study suggests that anisodamine is a potent antiviral agent for treating COVID-19.

Pharmacokinetics and Metabolism of Traditional Chinese Medicine in the Treatment of COVID-19.

BACKGROUND: The outbreak of coronavirus disease 19 (COVID-19) has caused great concern to public health. Convincing clinical experiences showed that traditional Chinese medicine (TCM) has exhibited remarkable efficacy in the prevention, treatment and rehabilitation of COVID-19. The research on the treatment of COVID-19 disease with TCM mainly focused on the pharmacological effects and mechanistic analysis. However, the TCM's pharmacokinetics and potential herb-drug interaction in the treatment of COVID-19 are currently unclear. METHODS: This review summarizes the pharmacokinetics and characteristics of cytochrome P450 enzyme (CYP450) metabolism of TCM recommended in the Guidelines for diagnosis and treatment of coronavirus disease 2019 (trial version eighth), and meanwhile analyzes the potential interactions between TCM and western medicine. RESULTS: The pharmacokinetics of TCM mainly focused on preclinical pharmacokinetics, and fewer clinical pharmacokinetics research was reported. When TCM and western are both metabolized by CYP450 and coadministered, a potential herb-drug interaction might occur. CONCLUSION: Knowledge of the pharmacokinetics and metabolism of TCM is key to understanding rational TCM use of COVID-19 and developing antiviral TCM.

Scorpion-Shaped Zinc Porphyrins as Tetrafunctional TAR RNA Predators and HIV-1 Reverse Transcriptase Inhibitors.

HIV-1 reverse transcriptase (RT) inhibitors are fundamental to the discovery and development of anti-HIV drugs. Their main target is RT, and only a tiny number of them can bind to viral RNA. In this paper, five new Zn(II) porphyrin compounds were developed with different characters. ZnTPP4 has both the appearance and the functions of a scorpion with a rigid tail and stinger to selectively hunt HIV-1 TAR RNA based on the molecular recognition of hydrogen bonds, a fierce chelicera to bite RNA by metal coordination, mighty pedipalps to grasp the bound RNA by supramolecular inclusion, and a broad body maintaining the configuration of each functional area so that they can cooperate with each other and providing accommodation space for the bound RNA. This tetrafunctional Zn(II) porphyrin is relatively nontoxic to normal cells and can produce sensitive responses for RNA. Moreover, this work offers practical construction methodologies for medication of AIDS and other diseases closely related to RT like EBOV and SARS-CoV-2.

Polypyridyl ruthenium complexes as bifunctional TAR RNA binders and HIV-1 reverse transcriptase inhibitors.

Inhibitors of type 1 human immunodeficiency virus (HIV-1) reverse transcriptase are central to anti-HIV therapy. Most of their targets are enzymes, while very few could bind to viral RNA. Here we designed four new polypyridyl Ru(II) complexes, which could bind HIV-1 TAR RNA tightly and selectively by molecular recognition of hydrogen bonds, further stabilize the Ru(II)-RNA bound system by electrostatic attraction, and efficiently inhibit the Moloney murine leukemia virus (M-MuLV) and HIV-1 reverse transcriptase. The polypyridyl Ru(II) complexes also have physical and chemical advantages, including high chemical stability and photostability, sensitive spectroscopic responses to HIV TAR RNA, and low toxicity to normal cells. This work also provides valuable drug design strategies for acquired immune deficiency syndrome (AIDS) and other reverse transcriptase related disease research, such as hepatitis C virus (HCV), Ebola virus (EBOV), influenza A virus, and most recently the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

Terpyridyl ruthenium complexes as visible spectral probe for poly(A) RNA and bifunctional TAR RNA binders and HIV-1 reverse transcriptase inhibitors

HIV-1 reverse transcriptase (RT) inhibitors play essential role in anti-HIV therapy. The vast majority of them target the enzymes, while very few are able to bind to the viral RNA. Here we designed and synthesized two new terpyridyl Ru(II) complexes with HIV-1 TAR RNA binding groups. The complex RuTz2 exhibited a remarkable selectivity for poly(A) RNA over calf thymus DNA, total RNA and yeast transfer RNA, generated significant visible spectral response and inhibited the reverse transcription of poly(A) RNA to poly(dT) cDNA by M-MuLV RT. Moreover, RuTz2 was found to target the HIV-1 TAR RNA tightly and selectively by molecular recognition of hydrogen bonds, further stabilize the Ru(II)-RNA binding complex by electrostatic attraction, and efficiently inhibit the HIV-1 RT. These terpyridyl Ru(II) complexes also showed low toxicity to normal cells, which would greatly reduce its harmful side-effect on normal cells in drug application. This work also provides valuable drug design strategies for AIDS and other RT related diseases researches, such as HCV, EBOV and SARS-CoV-2.

Associations among perceived built environment, attitudes, walking behavior, and physical and mental state of college students during COVID-19.

Owing to strict access control implemented on university campuses during COVID-19, college students experienced increased isolation, resulting in several physical and mental health issues. This study investigates the relationships among perceived built environment, walking attitudes, walking behavior, physical and mental state, and the impact of COVID-19. A cross-sectional survey was conducted among undergraduate students (N = 429) at Dalian University of Technology, China, on September 20 (Sunday) and 21 (Monday), 2020. The survey questionnaire included questions related to socio-demographic factors, perceived environment (accessibility, road condition and safety, and aesthetics), walking attitudes, walking behavior (number of walking trips), physical and mental state, and the impact of pandemic. Subsequently, two structural equation models (SEMs) were developed to analyze the proposed conceptual framework. The empirical results indicated that the SEMs fit the data well, thereby validating the conceptual framework. Perceived environment (especially accessibility), attitudes, and walking behavior significantly influenced physical and mental state. Perceived environment mediated the effects between attitudes and walking behavior and physical and mental state. The pandemic negatively impacted attitudes and physical and mental state. The effect of perceived accessibility on walking behavior and that of walking behavior on physical and mental state were stronger on weekends, whereas the effects of attitudes and the pandemic on physical and mental state were stronger on weekdays. The findings indicate that universities should implement appropriate strategies to improve the objective and subjective built environment, especially accessibility, and cultivate positive attitudes among students to promote walking and improve physical and mental health during COVID-19.

Advanced graph and sequence neural networks for molecular property prediction and drug discovery.

MOTIVATION: Properties of molecules are indicative of their functions and thus are useful in many applications. With the advances of deep-learning methods, computational approaches for predicting molecular properties are gaining increasing momentum. However, there lacks customized and advanced methods and comprehensive tools for this task currently. RESULTS: Here, we develop a suite of comprehensive machine-learning methods and tools spanning different computational models, molecular representations and loss functions for molecular property prediction and drug discovery. Specifically, we represent molecules as both graphs and sequences. Built on these representations, we develop novel deep models for learning from molecular graphs and sequences. In order to learn effectively from highly imbalanced datasets, we develop advanced loss functions that optimize areas under precision-recall curves (PRCs) and receiver operating characteristic (ROC) curves. Altogether, our work not only serves as a comprehensive tool, but also contributes toward developing novel and advanced graph and sequence-learning methodologies. Results on both online and offline antibiotics discovery and molecular property prediction tasks show that our methods achieve consistent improvements over prior methods. In particular, our methods achieve #1 ranking in terms of both ROC-AUC (area under curve) and PRC-AUC on the AI Cures open challenge for drug discovery related to COVID-19. AVAILABILITY AND IMPLEMENTATION: Our source code is released as part of the MoleculeX library (https://github.com/divelab/MoleculeX) under AdvProp. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Etiological and epidemiological features of acute respiratory infections in China.

Nationwide prospective surveillance of all-age patients with acute respiratory infections was conducted in China between 2009‒2019. Here we report the etiological and epidemiological features of the 231,107 eligible patients enrolled in this analysis. Children <5 years old and school-age children have the highest viral positivity rate (46.9%) and bacterial positivity rate (30.9%). Influenza virus, respiratory syncytial virus and human rhinovirus are the three leading viral pathogens with proportions of 28.5%, 16.8% and 16.7%, and Streptococcus pneumoniae, Mycoplasma pneumoniae and Klebsiella pneumoniae are the three leading bacterial pathogens (29.9%, 18.6% and 15.8%). Negative interactions between viruses and positive interactions between viral and bacterial pathogens are common. A Join-Point analysis reveals the age-specific positivity rate and how this varied for individual pathogens. These data indicate that differential priorities for diagnosis, prevention and control should be highlighted in terms of acute respiratory tract infection patients' demography, geographic locations and season of illness in China.

Basic Reproduction Number of the 2019 Novel Coronavirus Disease in the Major Endemic Areas of China: A Latent Profile Analysis.

Objective: The aim of this study is to analyze the latent class of basic reproduction number (R0) trends of the 2019 novel coronavirus disease (COVID-19) in the major endemic areas of China. Methods: The provinces that reported more than 500 cases of COVID-19 till February 18, 2020 were selected as the major endemic areas. The Verhulst model was used to fit the growth rate of cumulative confirmed cases. The R0 of COVID-19 was calculated using the parameters of severe acute respiratory syndrome (SARS) and COVID-19. The latent class of R0 was analyzed using the latent profile analysis (LPA) model. Results: The median R0 calculated from the SARS and COVID-19 parameters were 1.84-3.18 and 1.74-2.91, respectively. The R0 calculated from the SARS parameters was greater than that calculated from the COVID-19 parameters (Z = -4.782 to -4.623, p < 0.01). Both R0 can be divided into three latent classes. The initial value of R0 in class 1 (Shandong Province, Sichuan Province, and Chongqing Municipality) was relatively low and decreased slowly. The initial value of R0 in class 2 (Anhui Province, Hunan Province, Jiangxi Province, Henan Province, Zhejiang Province, Guangdong Province, and Jiangsu Province) was relatively high and decreased rapidly. Moreover, the initial R0 value of class 3 (Hubei Province) was in the range between that of classes 1 and 2, but the higher R0 level lasted longer and decreased slowly. Conclusion: The results indicated that the overall R0 trend is decreased with the strengthening of comprehensive prevention and control measures of China for COVID-19, however, there are regional differences.

Outcomes of atrial fibrillation in patients with COVID-19 pneumonia: A systematic review and meta-analysis.

BACKGROUND: Recently, emerging evidence has suggested that atrial fibrillation (AF) has an epidemiological correlation with coronavirus disease 2019 (COVID-19). However, the clinical outcomes of AF in COVID-19 remain inconsistent and inconclusive. The aim of this study was to provide a comprehensive description of the impact of AF on the prognosis of patients with COVID-19 pneumonia. METHODS: Three electronic databases (PubMed, Embase, and Web of Science) were searched for eligible studies as of March 1, 2021. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were used to evaluate the associations between AF (preexisting and new-onset) and in-hospital mortality, post-discharge mortality, and ventilator use. RESULTS: A total of 36 individual studies were incorporated into our meta-analysis. The combined results revealed that preexisting AF was associated with increased in-hospital mortality (pooled OR: 2.07; 95% CI: 1.60-2.67; p < 0.001), post-discharge mortality (pooled OR: 2.69; 95% CI: 1.24-5.83; p < 0.05), and ventilator utilization (pooled OR: 4.53; 95% CI: 1.33-15.38; p < 0.05) in patients with COVID-19. In addition, our data demonstrated that new-onset AF during severe acute respiratory syndrome coronavirus 2 infection was significantly correlated with increased mortality (pooled OR: 2.38; 95% CI: 2.04-2.77; p < 0.001). CONCLUSIONS: The presence of AF is correlated with adverse outcomes in patients with COVID-19 pneumonia, which deserves increased attention and should be managed appropriately to prevent adverse outcomes.

Home-Use and Real-Time Sleep-Staging System Based on Eye Masks and Mobile Devices with a Deep Learning Model.

PURPOSE: Sleep is an important human activity. Comfortable sensing and accurate analysis in sleep monitoring is beneficial to many healthcare and medical applications. From 2020, owing to the COVID­19 pandemic that spreads between people when they come into close physical contact with one another, the willingness to go to hospital for receiving care has reduced; care-at-home is the trend in modern healthcare. Therefore, a home-use and real-time sleep-staging system is developed in this paper. METHODS: We developed and implemented a real-time sleep staging system that integrates a wearable eye mask for high-quality electroencephalogram/electrooculogram measurement and a mobile device with MobileNETV2 deep learning model for sleep-stage identification. In the experiments, 25 all-night recordings were acquired, 17 of which were used for training, and the remaining eight were used for testing. RESULTS: The averaged scoring agreements for the wake, light sleep, deep sleep, and rapid eye movement stages were 85.20%, 87.17%, 82.87%, and 89.30%, respectively, for our system compared with the manual scoring of PSG recordings. In addition, the mean absolute errors of four objective sleep measurements, including sleep efficiency, total sleep time, sleep onset time, and wake after sleep onset time were 1.68%, 7.56 min, 5.50 min, and 3.94 min, respectively. No significant differences were observed between the proposed system and manual PSG scoring in terms of the percentage of each stage and the objective sleep measurements. CONCLUSION: These experimental results demonstrate that our system provides high scoring agreements in sleep staging and unbiased sleep measurements owing to the use of EEG and EOG signals and powerful mobile computing based on deep learning networks. These results also suggest that our system is applicable for home-use real-time sleep monitoring.

Intracellular autoactivation of TMPRSS11A, an airway epithelial transmembrane serine protease.

Type II transmembrane serine proteases (TTSPs) are a group of enzymes participating in diverse biological processes. Some members of the TTSP family are implicated in viral infection. TMPRSS11A is a TTSP expressed on the surface of airway epithelial cells, which has been shown to cleave and activate spike proteins of the severe acute respiratory syndrome (SARS) and the Middle East respiratory syndrome coronaviruses (CoVs). In this study, we examined the mechanism underlying the activation cleavage of TMPRSS11A that converts the one-chain zymogen to a two-chain enzyme. By expression in human embryonic kidney 293, esophageal EC9706, and lung epithelial A549 and 16HBE cells, Western blotting, and site-directed mutagenesis, we found that the activation cleavage of human TMPRSS11A was mediated by autocatalysis. Moreover, we found that TMPRSS11A activation cleavage occurred before the protein reached the cell surface, as indicated by studies with trypsin digestion to remove cell surface proteins, treatment with cell organelle-disturbing agents to block intracellular protein trafficking, and analysis of a soluble form of TMPRSS11A without the transmembrane domain. We also showed that TMPRSS11A was able to cleave the SARS-CoV-2 spike protein. These results reveal an intracellular autocleavage mechanism in TMPRSS11A zymogen activation, which differs from the extracellular zymogen activation reported in other TTSPs. These findings provide new insights into the diverse mechanisms in regulating TTSP activation.

Clinical Characteristics of 195 Cases of COVID-19 with Gastrointestinal Symptoms COVID-19 with Gastrointestinal Symptoms.

BACKGROUND: Patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), have fever, dry cough, dyspnea, and fatigue. The disease has now become a global pandemic. The purpose of this study was to explore the relationship between COVID-19 and gastrointestinal (GI) symptoms. METHODS: We collected and analyzed data on patients with laboratory-confirmed COVID-19 by high-throughput sequencing or reverse transcription-polymerase chain reaction. We reviewed electronic medical records of 405 hospitalized COVID-19 patients in the Third Hospital of Wuhan. RESULTS: Among the 405 confirmed patients, 210 had no GI symptoms, 195 had GI symptoms, and the first symptom of 155 patients was GI. The prevalence of vascular and digestive diseases in the group with GI symptoms was significantly higher than in the group without GI symptoms. In patients with GI symptoms, the proportion with fever, cough, dysphoria, chest tightness, poor appetite, chest pain, and pharyngeal pain was significantly higher than in those without GI symptoms. There was no significant difference in imaging between the 2 groups. In patients with GI symptoms, the proportion with increased procalcitonin (PCT) level and decreased lymphocyte count was significantly higher than in those without GI symptoms. CONCLUSION: COVID-19 patients with GI symptoms had significantly more vascular and digestive system diseases and were more likely to have clinical manifestations of fever, cough, poor appetite, chest tightness, chest pain, insomnia, and pharyngeal pain. There were more patients with diarrhea, nausea, and vomiting. Patients with GI symptoms were more likely to have increased PCT and decreased lymphocyte count.

Heating behavior using household air-conditioners during the COVID-19 lockdown in Wuhan: An exploratory and comparative study.

Wuhan is located in China's hot summer and cold winter (HSCW) zone, where the average temperature of the city from January to February 2020 is only 6.6 °C. This study aimed to explore and compare the air conditioner (AC) heating behavior of Wuhan residents before and after the COVID-19 lockdown. The date of commencement of the Wuhan lockdown (January 23, 2020) was considered the demarcation point to divide the AC monitoring data from the Internet of Things cloud platform into two groups; before and after Wuhan lockdown. Statistical methods were applied to analyze AC heating behavior of Wuhan residents from a total of 378 air conditioners during these two periods. The daily AC usage rate and average daily AC usage duration following the lockdown had a stronger correlation with daily outdoor temperature than that before the lockdown. AC heating behavior continued to demonstrate a part-time intermittent operation during the lockdown period, despite residents staying at home for a longer period. Trigger temperatures for occupants to turn on or adjust their AC during the lockdown period were overall 1-2 °C higher than before the lockdown. The AC heating demand in the HSCW zone has been increasing in recent years. These research results inform research on household energy demand and thermal comfort in China's HSCW zone, and provide a reference on the household behavioral changes in the occupants in the context of a lockdown as a result of the global COVID-19 pandemic.